Identifying the Factors Associated With Inpatient Admissions for Non-COVID-19 Illnesses

Abstract

Declining inpatient admissions have serious consequences on hospital financial stability as well as the health of patients. Thus, identifying factors associated with inpatient admissions is crucial to properly manage healthcare services. The major objective of this research is to demonstrate a systematic methodology using regression analysis and no free lunch (NFL) theorem to identify the most significant factors associated with non-COVID-19 ADMs and to identify which of them have deviated from an ideal state of service. This research uses Pennsylvania U.S. hospital data from 2003 to 2018 and identified that bed setup, staffed and supported, average length of stay, occupancy rate, readmission index, and outpatients are significantly associated with ADMs. Further, readmissions and outpatient admissions are found with an unusual association compared to an ideal condition. This paper discusses the steps that U.S. healthcare systems have already implemented and presents improvement recommendations.